mlsanityData to 7 Oct 2026

Deep Retinal Image Understanding

arXiv 1609.01103 ↗First posted 5 Sep 2016cs.CVcited by 35

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Abstract (arXiv)

This paper presents Deep Retinal Image Understanding (DRIU), a unified framework of retinal image analysis that provides both retinal vessel and optic disc segmentation. We make use of deep Convolutional Neural Networks (CNNs), which have proven revolutionary in other fields of computer vision such as object detection and image classification, and we bring their power to the study of eye fundus images. DRIU uses a base network architecture on which two set of specialized layers are trained to solve both the retinal vessel and optic disc segmentation. We present experimental validation, both qualitative and quantitative, in four public datasets for these tasks. In all of them, DRIU presents super-human performance, that is, it shows results more consistent with a gold standard than a second human annotator used as control.

Key facts. Cited by 35 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Sep 2016.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 11; 2022: 10; 2023: 5; 2024: 4; 2025: 3; 2026: 2.

35 papers.

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  1. 2021Applications of Deep Learning in Fundus Images: A Reviewcited by 59
  2. 2021Uncertainty guided semi-supervised segmentation of retinal layers in OCT imagescited by 29
  3. 2022AADG: Automatic Augmentation for Domain Generalization on Retinal Image Segmentationcited by 18
  4. 2021Sequential vessel segmentation via deep channel attention networkcited by 14
  5. 2022MKIS-Net: A Light-Weight Multi-Kernel Network for Medical Image Segmentationcited by 13
  6. 2021RC-Net: A Convolutional Neural Network for Retinal Vessel Segmentationcited by 12
  7. 2022Local Intensity Order Transformation for Robust Curvilinear Object Segmentationcited by 12
  8. 2023Feature Enhancer Segmentation Network (FES-Net) for Vessel Segmentationcited by 10
  9. 2023ESDMR-Net: A Lightweight Network With Expand-Squeeze and Dual Multiscale Residual Connections for Medical Image Segmentationcited by 9
  10. 2024Advancing Medical Image Segmentation with Mini-Net: A Lightweight Solution Tailored for Efficient Segmentation of Medical Imagescited by 9
  11. 2022Orientation and Context Entangled Network for Retinal Vessel Segmentationcited by 8
  12. 2021DR-VNet: Retinal Vessel Segmentation via Dense Residual UNetcited by 6
23 more
  1. 2021An Analysis of the Influence of Transfer Learning When Measuring the Tortuosity of Blood Vesselscited by 4
  2. 2022Enforcing connectivity of 3D linear structures using their 2D projectionscited by 3
  3. 2022Affinity Feature Strengthening for Accurate, Complete and Robust Vessel Segmentationcited by 3
  4. 2023MEMO: Dataset and Methods for Robust Multimodal Retinal Image Registration with Large or Small Vessel Density Differencescited by 3
  5. 2025Universal Vessel Segmentation for Multi-Modality Retinal Imagescited by 3
  6. 2021Dive into Layers: Neural Network Capacity Bounding using Algebraic Geometrycited by 2
  7. 2021Optic Disc Segmentation using Disk-Centered Patch Augmentationcited by 2
  8. 2022Weakly-supervised detection of AMD-related lesions in color fundus images using explainable deep learningcited by 2
  9. 2023SCOPE: Structural Continuity Preservation for Medical Image Segmentationcited by 2
  10. 2024Retinal Vessel Segmentation with Deep Graph and Capsule Reasoningcited by 2
  11. 2025CAPE: Connectivity-Aware Path Enforcement Loss for Curvilinear Structure Delineationcited by 2
  12. 2021A Deep Learning-Based Unified Framework for Red Lesions Detection on Retinal Fundus Imagescited by 1
  13. 2021Adjusting the Ground Truth Annotations for Connectivity-Based Learning to Delineatecited by 1
  14. 2023Robust Unsupervised Domain Adaptation by Retaining Confident Entropy via Edge Concatenationcited by 1
  15. 2021Automated airway segmentation by learning graphical structurecited by 0
  16. 2022A Graphical Approach For Brain Haemorrhage Segmentationcited by 0
  17. 2022A comprehensive survey on computer-aided diagnostic systems in diabetic retinopathy screeningcited by 0
  18. 2022Introduction to Machine Learning for Physicians: A Survival Guide for Data Delugecited by 0
  19. 2024TransResNet: Integrating the Strengths of ViTs and CNNs for High Resolution Medical Image Segmentation via Feature Graftingcited by 0
  20. 2024TransUNext: towards a more advanced U-shaped framework for automatic vessel segmentation in the fundus imagecited by 0
  21. 2025A Deep Convolutional Neural Network-Based Novel Class Balancing for Imbalance Data Segmentationcited by 0
  22. 2026D-Convexity: A Unified Differentiable Convex Shape Prior via Quasi-Concavity for Data-driven Image Segmentationcited by 0
  23. 2026Observer Choice and Threshold Selection in Retinal Vessel Segmentation: A Subject-Separated Evaluationcited by 0